Landslide susceptibility mapping in parts of Aglar watershed, Lesser Himalaya based on frequency ratio method in GIS environment

The Himalayan Mountain range is prone to landslides and its influential factors vary from region to region. To identify these factors, it is essential to have comprehensive information about the study area. This study aims to assess Landslide Susceptibility Mapping in parts of the Aglar watershed in the Lesser Himalayas using the frequency ratio method in the GIS environment. An inventory map in the first place of landslide events was prepared using satellite data and field survey studies. In this study, pertinently, sixteen conditioning factors were considered as slope, aspect, profile curvature, plan curvature, elevation, relative relief, geology, distance to stream, distance to road, normalized difference vegetation index, stream power index, topographic wetness index, rainfall, distance to lineaments, geomorphology, and land use land cover based on the local topography and climate. To gain a comprehensive understanding of the study area, subsequently, the frequency ratio of each factor was analyzed. This determined the correlation between landslide classes and each class of conditioning factors. A thorough analysis was conducted to select the most significant factors using the higher and lower prediction ratio values. This study was eventually conducted by comparing three susceptibility maps that were created based on prediction ratio values. To confirm the comparison, the ROC–AUC curve was utilized. The accuracy of the results was evaluated through a prediction rate and success rate curve, resulting in 78.5 and 80.7%, respectively, demonstrating a commendable performance. In this paper, the significance of different conditioning factors is evident in the increase of the very high susceptible area from 2.44 to 5.99% and eventually to 8.44%.